Aarhus University Seal / Aarhus Universitets segl

The ideal number of lemmas in an ideal accounting dictionary

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Lemma lacunas in dictionaries are a traditional focus area for lexicographers, but the opposite problem, which we choose to call lemma flooding, has received very little attention. The study of this flooding could be relevant in order to save lexicographers spending thousands of hours producing dictionary entries which nobody reads.
In Bergenholtz/Norddahl (2012) we showed that during a three-year period less than 33% of all dictionary articles out of 18 million dictionary consultations were consulted in a dictionary with 111.000 entries. We examined nine possible reasons why a given word might not be of interest to users and consequently could be ignored in order to avoid lemma flooding. We tried to demonstrate that while it is not possible to completely avoid lemma flooding, implementing a relatively simple rule could minimize it. But in reality the results were quite disappointing, because there were no clear rules or methods to avoid lemma flooding.
Now we will try the same kind of analysis of log files for the English-Danish and the Danish-English Accounting Dictionaries. We see here that there are differences between different dictionaries (monolingual for English and Danish and bilingual for English-Danish and Danish-English). We will try to give some explanations, but must admit beforehand that we have not found satisfying explanations which could lead to a plan for future accounting dictionaries or other economic dictionaries thus avoiding the production of never used dictionary articles.
Original languageEnglish
JournalHermes
Volume53
Pages (from-to)143-150
Number of pages8
ISSN0904-1699
Publication statusPublished - 2014

    Research areas

  • lemma selection, lemma lacuna, lemma flooding, lemma stock, liog file

See relations at Aarhus University Citationformats

ID: 89938693